Description
- 3+ years of non-internship professional software development experience
- 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience
- Experience programming with at least one software programming language
- Experience working with Data & AI related technologies, including, but not limited to, AI/ML, GenAI, Analytics, Database, and/or Storage
- Experience working with customers with a passion for delivering exceptional service, or experience that includes strong analytical skills, attention to detail, and effective communication abilities and experience in software development
- Computer Science core: object-oriented design, data structures, and performance analysis with at least 2 programming languages.
- Experience in one or more of the following areas: ML compilers, production coding agents, GenAI model architecture, model training, neural network optimization, or alternatively applied math.
- 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
- 2+ years in machine learning or other computational modeling environments with an emphasis on hosting, building or optimizing models for diverse hardware platforms
- Proven track record in building AI agents that automate ML workload optimization, ML compiler tuning, distributed inference and training, or ML kernel authoring and optimization
- Experience working with open-source software communities in the optimization space or related areas
- Knowledge of the state-of-the-art technology used in the Machine Learning space and its mathematical underpinning
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
USA, NY, New York - 158,100.00 - 213,800.00 USD annually
About the Team
The Neuroboros team was recently created to pursue the ambitious goal of leveraging and expanding Generative AI technologies to help customers benefit from the scale and price/performance equation offered by Amazon Machine Learning hardware. The creation of the team in NYC is key to Annapurna Labs’ location strategy, with the goal of creating an additional hub attracting top talent with varied backgrounds to work on challenging problems, using and building state-of-the-art tooling.
About Amazon Annapurna Labs:
Amazon Annapurna Labs team (our organization within AWS UC) is responsible for building innovation in silicon and software for our AWS customers. We are at the forefront of innovation by combining cloud scale with the world’s most talented engineers. Our team covers multiple disciplines including silicon engineering, hardware design, software and operations. Because of our team’s breadth of talent, we have been able to improve AWS cloud infrastructure in high-performance machine learning with AWS Neuron, Inferentia and Trainium ML chips, in networking and security with products such as AWS Nitro, Enhanced Network Adapter (ENA), and Elastic Fabric Adapter (EFA), and in computing with AWS Graviton and F1 EC2 instances.
About AWS
Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.
About AWS Neuron:
AWS Neuron is the software of Trainium and Inferentia, the AWS Machine Learning chips. Inferentia delivers best-in-class ML inference performance at the lowest cost in the cloud to our AWS customers. Trainium is designed to deliver the best-in-class ML training performance at the lowest training cost in the cloud, and it’s all being enabled by AWS Neuron. Neuron is a Software that include ML compiler and native integration into popular ML frameworks. Our products are being used at scale with external customers like Anthropic and Databricks as well as internal customers like Alexa, Amazon Bedrock, Amazon Robotics, Amazon Ads, Amazon Rekognition and many more.
Job Summary
You will join a dynamic team working at the cutting edge of the GenAI revolution by applying AI to AI. You will work on building agents, tools, and models to simplify and accelerate customer adoption of Neuron, the software stack supporting Amazon's Machine Learning silicon: Trainium. Partnering with external and internal customers, you will identify key obstacles and opportunities to accelerate their migration to AWS's ML silicon. You will be a key contributor driving impact by building AI agents and tools that simplify AWS Neuron adoption, which is critical to AWS's Generative AI business.
Key job responsibilities
This role requires collaborating with other Neuron Software teams, Science, AWS AI Services, external partners and customers with a potential high impact on AWS's top and bottom line. As a member of the team applying Generative AI to accelerate Neuron adoption, you will play a key role in shaping this space with the following technical responsibilities:
- Research implementations that deliver the best possible experiences for customers.
- Deliver on goals to improve the time and effort it takes to port and optimize Machine Learning workloads on Neuron.
- Solve challenging technical problems, often ones not solved before, at every layer of the stack
- Design, implement, test, deploy and maintain innovative software solutions to transform service performance, durability, cost, and security.
- Build high-quality, highly available, always-on products.
- Potentially contribute intellectual property through patents
A day in the life
As you design and code solutions to help our team drive efficiencies in software architecture, you’ll create metrics, implement automation and other improvements, and resolve the root cause of software defects. You’ll also:
- Build high-impact solutions to deliver to our large customer base.
- Participate in design discussions, code review, and communicate with internal and external stakeholders.
- Work cross-functionally to help drive business decisions with your technical input. You will collaborate closely with a cross-functional team comprised of compiler, hardware, and ML engineers.
- Work in a startup-like development environment, where you’re always working on the most important stuff.
- 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience
- Experience programming with at least one software programming language
- Experience working with Data & AI related technologies, including, but not limited to, AI/ML, GenAI, Analytics, Database, and/or Storage
- Experience working with customers with a passion for delivering exceptional service, or experience that includes strong analytical skills, attention to detail, and effective communication abilities and experience in software development
- Computer Science core: object-oriented design, data structures, and performance analysis with at least 2 programming languages.
- Experience in one or more of the following areas: ML compilers, production coding agents, GenAI model architecture, model training, neural network optimization, or alternatively applied math.
- 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
- 2+ years in machine learning or other computational modeling environments with an emphasis on hosting, building or optimizing models for diverse hardware platforms
- Proven track record in building AI agents that automate ML workload optimization, ML compiler tuning, distributed inference and training, or ML kernel authoring and optimization
- Experience working with open-source software communities in the optimization space or related areas
- Knowledge of the state-of-the-art technology used in the Machine Learning space and its mathematical underpinning
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
USA, NY, New York - 158,100.00 - 213,800.00 USD annually
About the Team
The Neuroboros team was recently created to pursue the ambitious goal of leveraging and expanding Generative AI technologies to help customers benefit from the scale and price/performance equation offered by Amazon Machine Learning hardware. The creation of the team in NYC is key to Annapurna Labs’ location strategy, with the goal of creating an additional hub attracting top talent with varied backgrounds to work on challenging problems, using and building state-of-the-art tooling.
About Amazon Annapurna Labs:
Amazon Annapurna Labs team (our organization within AWS UC) is responsible for building innovation in silicon and software for our AWS customers. We are at the forefront of innovation by combining cloud scale with the world’s most talented engineers. Our team covers multiple disciplines including silicon engineering, hardware design, software and operations. Because of our team’s breadth of talent, we have been able to improve AWS cloud infrastructure in high-performance machine learning with AWS Neuron, Inferentia and Trainium ML chips, in networking and security with products such as AWS Nitro, Enhanced Network Adapter (ENA), and Elastic Fabric Adapter (EFA), and in computing with AWS Graviton and F1 EC2 instances.
About AWS
Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.
About AWS Neuron:
AWS Neuron is the software of Trainium and Inferentia, the AWS Machine Learning chips. Inferentia delivers best-in-class ML inference performance at the lowest cost in the cloud to our AWS customers. Trainium is designed to deliver the best-in-class ML training performance at the lowest training cost in the cloud, and it’s all being enabled by AWS Neuron. Neuron is a Software that include ML compiler and native integration into popular ML frameworks. Our products are being used at scale with external customers like Anthropic and Databricks as well as internal customers like Alexa, Amazon Bedrock, Amazon Robotics, Amazon Ads, Amazon Rekognition and many more.
Job Summary
You will join a dynamic team working at the cutting edge of the GenAI revolution by applying AI to AI. You will work on building agents, tools, and models to simplify and accelerate customer adoption of Neuron, the software stack supporting Amazon's Machine Learning silicon: Trainium. Partnering with external and internal customers, you will identify key obstacles and opportunities to accelerate their migration to AWS's ML silicon. You will be a key contributor driving impact by building AI agents and tools that simplify AWS Neuron adoption, which is critical to AWS's Generative AI business.
Key job responsibilities
This role requires collaborating with other Neuron Software teams, Science, AWS AI Services, external partners and customers with a potential high impact on AWS's top and bottom line. As a member of the team applying Generative AI to accelerate Neuron adoption, you will play a key role in shaping this space with the following technical responsibilities:
- Research implementations that deliver the best possible experiences for customers.
- Deliver on goals to improve the time and effort it takes to port and optimize Machine Learning workloads on Neuron.
- Solve challenging technical problems, often ones not solved before, at every layer of the stack
- Design, implement, test, deploy and maintain innovative software solutions to transform service performance, durability, cost, and security.
- Build high-quality, highly available, always-on products.
- Potentially contribute intellectual property through patents
A day in the life
As you design and code solutions to help our team drive efficiencies in software architecture, you’ll create metrics, implement automation and other improvements, and resolve the root cause of software defects. You’ll also:
- Build high-impact solutions to deliver to our large customer base.
- Participate in design discussions, code review, and communicate with internal and external stakeholders.
- Work cross-functionally to help drive business decisions with your technical input. You will collaborate closely with a cross-functional team comprised of compiler, hardware, and ML engineers.
- Work in a startup-like development environment, where you’re always working on the most important stuff.
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